#prompt-engineering

Validate and retry LLM outputs for ruby_llm. Describe the JSON response you expect, fall back to a stronger model when the cheaper one fails the rules, and gate CI on regressions — all as one contract object per step.

The official CLI for the PromptVM platform

Your prompts need tests too. Run prompts against real datasets, score outputs with LLM judges, version everything, and compare runs to see what got better.

AI development toolkit for Claude Code — ideate, auto-resolve, and ship with context engineering and agent orchestration

Typed building blocks for everything around your LLM call.

Prompt refinement and workflow orchestration for Codex: turn vague ideas into scoped goals, reviewable SPECs, validation evidence, and PR-ready handoffs.

An opinionated agentic development layer for OpenCode — spec-first when it matters, review-driven execution, portable model roles, safer tools, and long-run safety.

21 writing rules for AI coding and writing agents. Drop-in for Claude Code, Codex, Copilot, Cursor, and Aider, so their output reads like a tech pro.